rename_if()
, rename_at()
, and rename_all()
have been superseded by
rename_with()
. The matching select statements have been superseded by the
combination of a select()
+ rename_with()
.
These functions were superseded because mutate_if()
and friends were
superseded by across()
. select_if()
and rename_if()
already use tidy
selection so they can't be replaced by across()
and instead we need a new
function.
select_all(.tbl, .funs = list(), ...) rename_all(.tbl, .funs = list(), ...) select_if(.tbl, .predicate, .funs = list(), ...) rename_if(.tbl, .predicate, .funs = list(), ...) select_at(.tbl, .vars, .funs = list(), ...) rename_at(.tbl, .vars, .funs = list(), ...)
.tbl | A |
---|---|
.funs | A function |
... | Additional arguments for the function calls in
|
.predicate | A predicate function to be applied to the columns
or a logical vector. The variables for which |
.vars | A list of columns generated by |
#> # A tibble: 32 x 11 #> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows#> # A tibble: 32 x 11 #> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows# NB: the transformation comes first in rename_with is_whole <- function(x) all(floor(x) == x) mtcars %>% rename_if(is_whole, toupper)#> # A tibble: 32 x 11 #> mpg CYL disp HP drat wt qsec VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows#> # A tibble: 32 x 11 #> mpg CYL disp HP drat wt qsec VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows#> # A tibble: 32 x 11 #> MPG CYL DISP HP drat wt qsec vs am gear carb #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows#> # A tibble: 32 x 11 #> MPG CYL DISP HP drat wt qsec vs am gear carb #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows# You now must select() and then rename mtcars %>% select_all(toupper)#> # A tibble: 32 x 11 #> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows#> # A tibble: 32 x 11 #> MPG CYL DISP HP DRAT WT QSEC VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 4 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 3 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 3 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 3 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 3 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 4 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 4 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 4 #> # … with 22 more rows# Selection drops unselected variables: mtcars %>% select_if(is_whole, toupper)#> # A tibble: 32 x 6 #> CYL HP VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 6 110 0 1 4 4 #> 2 6 110 0 1 4 4 #> 3 4 93 1 1 4 1 #> 4 6 110 1 0 3 1 #> 5 8 175 0 0 3 2 #> 6 6 105 1 0 3 1 #> 7 8 245 0 0 3 4 #> 8 4 62 1 0 4 2 #> 9 4 95 1 0 4 2 #> 10 6 123 1 0 4 4 #> # … with 22 more rows#> # A tibble: 32 x 6 #> CYL HP VS AM GEAR CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 6 110 0 1 4 4 #> 2 6 110 0 1 4 4 #> 3 4 93 1 1 4 1 #> 4 6 110 1 0 3 1 #> 5 8 175 0 0 3 2 #> 6 6 105 1 0 3 1 #> 7 8 245 0 0 3 4 #> 8 4 62 1 0 4 2 #> 9 4 95 1 0 4 2 #> 10 6 123 1 0 4 4 #> # … with 22 more rows#> # A tibble: 32 x 10 #> MPG CYL DISP HP DRAT WT QSEC VS AM CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 #> # … with 22 more rows#> # A tibble: 32 x 10 #> MPG CYL DISP HP DRAT WT QSEC VS AM CARB #> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> #> 1 21 6 160 110 3.9 2.62 16.5 0 1 4 #> 2 21 6 160 110 3.9 2.88 17.0 0 1 4 #> 3 22.8 4 108 93 3.85 2.32 18.6 1 1 1 #> 4 21.4 6 258 110 3.08 3.22 19.4 1 0 1 #> 5 18.7 8 360 175 3.15 3.44 17.0 0 0 2 #> 6 18.1 6 225 105 2.76 3.46 20.2 1 0 1 #> 7 14.3 8 360 245 3.21 3.57 15.8 0 0 4 #> 8 24.4 4 147. 62 3.69 3.19 20 1 0 2 #> 9 22.8 4 141. 95 3.92 3.15 22.9 1 0 2 #> 10 19.2 6 168. 123 3.92 3.44 18.3 1 0 4 #> # … with 22 more rows